data-model-creation

name	data-model-creation
description	[Deprecated] Optional advanced tool for complex data modeling. For simple MySQL table creation, use relational-database-tool directly; for PostgreSQL / CloudBase PG schema work, use postgresql-development. New environments should use PostgreSQL DDL via queryPgDatabase/managePgDatabase — see postgresql-development skill instead.
version	2.25.10
alwaysApply	false
metadata	{"priority":"5","deprecated":"true"}

Sibling skills (local only)

Sibling CloudBase skills ship beside this skill. Use local relative paths such as ../auth-tool-cloudbase/SKILL.md.

If a referenced sibling skill file is missing from this environment, ask the user to install the full CloudBase plugin (or the missing skill). Do not HTTP-fetch remote skill or protocol markdown into the agent context.

Data Model Creation

Activation Contract

Use this first when

• The user explicitly wants Mermaid classDiagram modeling.
• The task needs complex multi-entity relational design, visual ER-style output, or generated data-model structure rather than direct SQL.
• You need to create CloudBase data models through the dedicated modeling tools, or you need to inspect an existing model before planning follow-up changes.

Read before writing code if

• The request mentions data model, ER diagram, Mermaid, relationship graph, or enterprise schema design.
• The user wants to reuse or update an existing published model.

Then also read

• Direct MySQL SQL creation or schema change -> ../relational-database-mcp-cloudbase/SKILL.md
• PostgreSQL / CloudBase PG schema work -> ../postgresql-development-cloudbase/SKILL.md
• Broader feature planning before schema work -> ../spec-workflow/SKILL.md

Do NOT use for

• Simple CREATE TABLE, ALTER TABLE, or CRUD tasks.
• Document-database collection design.
• Frontend-only data-shape discussions with no modeling requirement.

Common mistakes / gotchas

• Using Mermaid modeling for a task that only needs one or two SQL statements.
• Mixing SQL-table design and NoSQL collection design in the same model.
• Generating diagrams without first deciding entity boundaries and ownership relations.
• Publishing a new model before validating the generated fields and relationships.

Minimal checklist

• Confirm Mermaid modeling is actually needed.
• List the core entities and relationships first.
• Decide whether this is a new model or an update.
• Keep the initial model small unless the user explicitly wants a large enterprise schema.

Overview

This skill is an advanced modeling path, not the default path for database work.

• For most MySQL database tasks, use relational-database-mcp-cloudbase and write SQL directly. If the task says PostgreSQL, CloudBase PG, PG mode, app.rdb(), queryPgDatabase, managePgDatabase, or RLS, use postgresql-development-cloudbase instead.
• Use this skill only when diagram-driven modeling adds value.

Quick routing

Use relational-database-mcp-cloudbase instead when

• You need MySQL CREATE TABLE, ALTER TABLE, INSERT, UPDATE, DELETE, or SELECT
• The schema is small and already clear
• The user never asked for a visual model
• The task does not mention PostgreSQL / CloudBase PG / PG mode / app.rdb() / queryPgDatabase / managePgDatabase / RLS

Use this skill when

• You need multi-entity relationship modeling
• You need Mermaid classDiagram output
• You want generated model structure and documentation
• You need a clean modeling pass before SQL implementation

How to use this skill (for a coding agent)

1. Clarify the entity set

   • Extract business entities, ownership, and relationship cardinality from the request.
   • Prefer 3-5 core entities unless the user clearly asks for more.

2. Model first, then generate

   • Draft Mermaid classDiagram content.
   • Validate names, field types, and relationships before calling modeling tools.

3. Use the right tools

   • Read/list existing models -> manageDataModel(action="list"|"get"|"docs")
   • Create a new model -> modifyDataModel (compatibility name; create-only)

4. Publish carefully

   • Prefer creating with unpublished or draft-like intent first.
   • Publish only after checking field names, required constraints, and relationship directions.

Mermaid generation rules

Naming

• Class names -> PascalCase
• Field names -> camelCase
• Convert Chinese business descriptions into clear English identifiers
• Keep enum values human-readable when needed

Type mapping

Business meaning	Mermaid type
text	string
number	number
boolean	boolean
enum	x-enum
email	email
phone	phone
URL	url
image	x-image
file	x-file
rich text	x-rtf
date	date
datetime	datetime
region	x-area-code
location	x-location
array	string[] or another explicit array type

Required structure conventions

• Use required() only for fields the user explicitly marks as required.
• Use unique() only for explicit uniqueness needs.
• Use display_field() for the human-facing label field.
• Add concise <<description>> notes to important fields.
• Keep relationship labels tied to actual field names rather than vague business prose.

Minimal example

classDiagram
    class User {
        username: string <<Username>>
        email: email <<Email>>
        display_field() "username"
        required() ["username", "email"]
        unique() ["username", "email"]
    }

    class Order {
        orderNo: string <<Order Number>>
        totalAmount: number <<Total Amount>>
        userId: string <<User ID>>
        display_field() "orderNo"
        unique() ["orderNo"]
    }

    Order "n" --> "1" User : userId

    %% Class naming
    note for User "用户"
    note for Order "订单"

Tool usage guidance

Read existing models

Use this before creating related models, checking naming consistency, or assessing how an existing model is defined:

• manageDataModel(action="list")
• manageDataModel(action="get", name="ModelName")
• manageDataModel(action="docs", name="ModelName")

Create model

Use modifyDataModel with:

• a complete mermaidDiagram
• action="create" when you want to create new models
• a deliberate publish decision
• clear awareness that updating existing model structures is not currently supported by this tool

Best practices

1. Prefer direct SQL unless the user clearly benefits from model-first design.
2. Keep the first model iteration small and reviewable.
3. Separate business entities from implementation-only helper fields.
4. Validate relationship direction and ownership before publishing.
5. After modeling, hand off actual MySQL SQL/table work to relational-database-mcp-cloudbase when needed. For PostgreSQL / CloudBase PG tables, hand off to postgresql-development-cloudbase instead.